Accurate forecasting of correlated time series have the potential to reveal holistic system dynamics of the underlying CPSs, including predicting future behavior [1]} and detecting anomalies [2]}, [3]}, which are important to enable effective operations of the CPSs.
For example, in an intelligent transportation system, analyzing speed time series enables travel
time forecasting, early warning of congestion, and predicting the effect of incidents, which help drivers make routing decisions [4]}, [5]}.
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